Control and Scheduling of the electricity demand in power supply systems
using time series forecasting is nowadays a powerful methodology used worldwide
in all power distribution systems. The main reason why it is so ...[+]

Control and Scheduling of the electricity demand in power supply systems
using time series forecasting is nowadays a powerful methodology used worldwide
in all power distribution systems. The main reason why it is so important
is very simple: The electricity cannot be saved in big quantities,
therefore the production and the consumption must match precisely, in order
not to waste energy and save costs. Time series forecasting is a very
powerful tool for power supply systems, and it is used worldwide by most of
the system regulators or network distributors to predict precisely the electricity
demand. These series use to show more than one seasonal pattern,
hence double seasonal exponential smoothing has become the best solution
for making forecasts for such kind of time series. Despite of this importance,
there isn't nowadays any software that deploys this seasonal model. The regulators
are demanding better tools in forecasting that capture this multiple
seasonal pattern, and the later works on double and triple seasonal exponential
smoothing seems to be a feasible solution. This project concentrates on
a MATLAB implementation of Taylor's double seasonal exponential smoothing
model, and explains its fundamentals and how it works. Later, it uses an
hourly recorded time series of electricity demand in Spain to draw conclusions
about the advantages of using this newer model for predictions.[-]